Competencies and objectives


Course context for academic year 2023-24

El aprendizaje automático es la rama de la inteligencia artificial que estudia cómo dotar a los computadores de la capacidad para aprender modelos de forma automática a partir de datos. En esta asignatura se pretende proporcionar una visión general de las técnicas más utilizadas en aprendizaje automático en sus tres paradigmas principales: aprendizaje supervisado, aprendizaje no supervisado y aprendizaje por refuerzo.



Course content (verified by ANECA in official undergraduate and Master’s degrees)

General Competences:>>Instrumental

  • CG1 : Advise on the choice, acquisition, and implementation of robotic and/or automated systems for different applications.
  • CG2 : Make decisions in the design and planning of a robotics and/or automation project, taking into account quality and environmental criteria.
  • CG3 : Implement and maintain robotics and/or automation projects that satisfy the requirements of industrial or service applications.
  • CG6 : Analyse, synthesise problems and make decisions.


General Competences:>>Interpersonal

  • CG10 : Critical reasoning.


General Competences:>>Systematic

  • CG12 : Capacity to apply the knowledge acquired to real situations.
  • CG13 : Capacity to work and learn autonomously.
  • CG14 : Capacity to adapt to new situations, promoting creativity and an entrepreneurial spirit.


Specific Competences:>>Robotics

  • CER010 : Conocer y saber aplicar las principales técnicas de aprendizaje y Deep learning en sistemas robóticos.


Specific Competences:>>Vision

  • CEVI5 : Conocer y aplicar métodos, técnicas e instrumentos de aprendizaje automático y Deep learning en visión artificial.


Specific Competences:>>Sensory

  • CESE4 : Analyse and optimise the design of a measurement acquisition system to obtain the required precision and accuracy.




Learning outcomes (Training objectives)

No data



Specific objectives stated by the academic staff for academic year 2023-24

No data





Code: 37818
Lecturer responsible:
Credits ECTS: 3,00
Theoretical credits: 0,44
Practical credits: 0,76
Distance-base hours: 1,80

Departments involved

    Theoretical credits: 0,44
    Practical credits: 0,76
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught